code: def apply_step(
      self, x, t, c_concat: list = None, c_crossattn: list = None
  ):
      if self.conditioning_key is None:
          out = self.diffusion_model(x, t)
      elif self.conditioning_key == "concat":
          xc = torch.cat([x] + c_concat, dim=1)
          out = self.diffusion_model(xc, t)
      elif self.conditioning_key == "crossattn":
          cc = torch.cat(c_crossattn, 1)
          out = self.diffusion_model(x, t, context=cc)
      elif self.conditioning_key == "hybrid":
          xc = torch.cat([x] + c_concat, dim=1)
          cc = torch.cat(c_crossattn, 1)
          out = self.diffusion_model(xc, t, context=cc)
      elif self.conditioning_key == "adm":
          cc = c_crossattn[0]
          out = self.diffusion_model(x, t, y=cc)
      else:
          raise NotImplementedError()
  
      return out
  
file_path: NeMo/nemo/collections/multimodal/models/text_to_image/dreambooth/util.py
imports: from functools import partial
  import numpy
  import torch
  import torch.nn
  from nemo.collections.multimodal.modules.stable_diffusion.diffusionmodules.util import extract_into_tensor, make_beta_schedule
  from nemo.collections.multimodal.parts.stable_diffusion.utils import default, exists
  from nemo.core.classes.common import Serialization
label_desc: Use image node_id 3 for calling the DiffusionWrapper obj's underlying member method code with example usage: obj.apply_step(x, t, c_concat, c_crossattn) and returns: out